Abstract

This paper describes a new method for linear spectral mixture analysis. Endmember spectra are only used as initial values in a least squares adjustment according to a Gauss-Markov model. The observations of the adjustment are the spectra of pixels in a pre-defined neighbourhood, the important result are improved endmember spectra. In a subsequent step the endmember percentages per pixel are derived using the MESMA approach. Using a level 1B ASTER satellite image of Burkina Faso the accuracy of the new model is compared to that of a standard unmixing approach. The new model predicts vegetation components considerably more accurate.